class_docstr: Fast Fourier Transform.
  
  .. TODO:
      The current implementation just works for matrix inputs, and permits
      taking a 1D FFT over either rows or columns. Add support for N-D FFTs
      as provided by either numpy or FFTW directly.
  
  .. TODO:
      Give the C code that uses FFTW.
  
  .. TODO:
      Unit tests.
class_docstr_tok: ["Fast","Fourier","Transform",".","..","TODO",":","The","current","implementation","just","works","for","matrix","inputs",",","and","permits","taking","a","1D","FFT","over","either","rows","or","columns",".","Add","support","for","N-D","FFTs","as","provided","by","either","numpy","or","FFTW","directly",".","..","TODO",":","Give","the","C","code","that","uses","FFTW",".","..","TODO",":","Unit","tests","."]
code: def __init__(self, half=False, inverse=False):
      self.half = half
      self.inverse = inverse
  
file_path: Theano/theano/sandbox/fourier.py
imports: from __future__ import absolute_import, print_function, division
  import numpy
  import numpy.fft
  from six.moves import xrange
  from theano import tensor
  from theano.gof import Op, Apply, generic
  import warnings
label_desc: Use image node_id 1 to create a new FFT object from inherited base classes: Op with example: obj = FFT(half, inverse)